Authorization and Governance for AI Agents: Runtime Authorization Beyond Identity at Scale
Designing Authorization‑Aware AI Agents at Scale Enforcing Runtime RBAC + ABAC with Approval Injection (JIT) Microsoft Entra Agent Identity enables organizations to govern and manage AI agent identities in Copilot Studio, improving visibility and identity-level control. However, as enterprises deploy multiple autonomous AI agents, identity and OAuth permissions alone cannot answer a more critical question: “Should this action be executed now, by this agent, for this user, under the current business and regulatory context?” This post introduces a reusable Authorization Fabric—combining a Policy Enforcement Point (PEP) and Policy Decision Point (PDP)—implemented as a Microsoft Entra‑protected endpoint using Azure Functions/App Service authentication. Every AI agent (Copilot Studio or AI Foundry/Semantic Kernel) calls this fabric before tool execution, receiving a deterministic runtime decision: ALLOW / DENY / REQUIRE_APPROVAL / MASK Who this is for Anyone building AI agents (Copilot Studio, AI Foundry/Semantic Kernel) that call tools, workflows, or APIs Organizations scaling to multiple agents and needing consistent runtime controls Teams operating in regulated or security‑sensitive environments, where decisions must be deterministic and auditable Why a V2? Identity is necessary—runtime authorization is missing Entra Agent Identity (preview) integrates Copilot Studio agents with Microsoft Entra so that newly created agents automatically get an Entra agent identity, manageable in the Entra admin center, and identity activity is logged in Entra. That solves who the agent is and improves identity governance visibility. But multi-agent deployments introduce a new risk class: Autonomous execution sprawl — many agents, operating with delegated privileges, invoking the same backends independently. OAuth and API permissions answer “can the agent call this API?” They do not answer “should the agent execute this action under business policy, compliance constraints, data boundaries, and approval thresholds?” This is where a runtime authorization decision plane becomes essential. The pattern: Microsoft Entra‑Protected Authorization Fabric (PEP + PDP) Instead of embedding RBAC logic independently inside every agent, use a shared fabric: PEP (Policy Enforcement Point): Gatekeeper invoked before any tool/action PDP (Policy Decision Point): Evaluates RBAC + ABAC + approval policies Decision output: ALLOW / DENY / REQUIRE_APPROVAL / MASK This Authorization Fabric functions as a shared enterprise control plane, decoupling authorization logic from individual agents and enforcing policies consistently across all autonomous execution paths. Architecture (POC reference architecture) Use a single runtime decision plane that sits between agents and tools. What’s important here Every agent (Copilot Studio or AI Foundry/SK) calls the Authorization Fabric API first The fabric is a protected endpoint (Microsoft Entra‑protected endpoint required) Tools (Graph/ERP/CRM/custom APIs) are invoked only after an ALLOW decision (or approval) Trust boundaries enforced by this architecture Agents never call business tools directly without a prior authorization decision The Authorization Fabric validates caller identity via Microsoft Entra Authorization decisions are centralized, consistent, and auditable Approval workflows act as a runtime “break-glass” control for high-impact actions This ensures identity, intent, and execution are independently enforced, rather than implicitly trusted. Runtime flow (Decision → Approval → Execution) Here is the runtime sequence as a simple flow (you can keep your Mermaid diagram too). ```mermaid flowchart TD START(["START"]) --> S1["[1] User Request"] S1 --> S2["[2] Agent Extracts Intent\n(action, resource, attributes)"] S2 --> S3["[3] Call /authorize\n(Entra protected)"] S3 --> S4 subgraph S4["[4] PDP Evaluation"] ABAC["ABAC: Tenant · Region · Data Sensitivity"] RBAC["RBAC: Entitlement Check"] Threshold["Approval Threshold"] ABAC --> RBAC --> Threshold end S4 --> Decision{"[5] Decision?"} Decision -->|"ALLOW"| Exec["Execute Tool / API"] Decision -->|"MASK"| Masked["Execute with Masked Data"] Decision -->|"DENY"| Block["Block Request"] Decision -->|"REQUIRE_APPROVAL"| Approve{"[6] Approval Flow"} Approve -->|"Approved"| Exec Approve -->|"Rejected"| Block Exec --> Audit["[7] Audit & Telemetry"] Masked --> Audit Block --> Audit Audit --> ENDNODE(["END"]) style START fill:#4A90D9,stroke:#333,color:#fff style ENDNODE fill:#4A90D9,stroke:#333,color:#fff style S1 fill:#5B5FC7,stroke:#333,color:#fff style S2 fill:#5B5FC7,stroke:#333,color:#fff style S3 fill:#E8A838,stroke:#333,color:#fff style S4 fill:#FFF3E0,stroke:#E8A838,stroke-width:2px style ABAC fill:#FCE4B2,stroke:#999 style RBAC fill:#FCE4B2,stroke:#999 style Threshold fill:#FCE4B2,stroke:#999 style Decision fill:#fff,stroke:#333 style Exec fill:#2ECC71,stroke:#333,color:#fff style Masked fill:#27AE60,stroke:#333,color:#fff style Block fill:#C0392B,stroke:#333,color:#fff style Approve fill:#F39C12,stroke:#333,color:#fff style Audit fill:#3498DB,stroke:#333,color:#fff ``` Design principle: No tool execution occurs until the Authorization Fabric returns ALLOW or REQUIRE_APPROVAL is satisfied via an approval workflow. Where Power Automate fits (important for readers) In most Copilot Studio implementations, Agents calls Power Automate (agent flows), is the practical integration layer that calls enterprise services and APIs. Copilot Studio supports “agent flows” as a way to extend agent capabilities with low-code workflows. For this pattern, Power Automate typically: acquires/uses the right identity context for the call (depending on your tenant setup), and calls the /authorize endpoint of the Authorization Fabric, returns the decision payload to the agent for branching. Copilot Studio also supports calling REST endpoints directly using the HTTP Request node, including passing headers such as Authorization: Bearer <token>. Protected endpoint only: Securing the Authorization Fabric with Microsoft Entra For this V2 pattern, the Authorization Fabric must be protected using Microsoft Entra‑protected endpoint on Azure Functions/App Service (built‑in auth). Microsoft Learn provides the configuration guidance for enabling Microsoft Entra as the authentication provider for Azure App Service / Azure Functions. Step 1 — Create the Authorization Fabric API (Azure Function) Expose an authorization endpoint: HTTP Step 2 — Enable Microsoft Entra‑protected endpoint on the Function App In Azure Portal: Function App → Authentication Add identity provider → Microsoft Choose Workforce configuration (enterprise tenant) Set Require authentication for all requests This ensures the Authorization Fabric is not callable without a valid Entra token. Step 3 — Optional hardening (recommended) Depending on enterprise posture, layer: IP restrictions / Private endpoints APIM in front of the Function for rate limiting, request normalization, centralized logging (For a POC, keep it minimal—add hardening incrementally.) Externalizing policy (so governance scales) To make this pattern reusable across multiple agents, policies should not be hardcoded inside each agent. Instead, store policy definitions in a central policy store such as Cosmos DB (or equivalent configuration store), and have the PDP load/evaluate policies at runtime. Why this matters: Policy changes apply across all agents instantly (no agent republish) Central governance + versioning + rollback becomes possible Audit and reporting become consistent across environments (For the POC, a single JSON document per policy pack in Cosmos DB is sufficient. For production, add versioning and staged rollout.) Store one PolicyPack JSON document per environment (dev/test/prod). Include version, effectiveFrom, priority for safe rollout/rollback. Minimal decision contract (standard request / response) To keep the fabric reusable across agents, standardize the request payload. Request payload (example) Decision response (deterministic) Example scenario (1 minute to understand) Scenario: A user asks a Finance agent to create a Purchase Order for 70,000. Even if the user has API permission and the agent can technically call the ERP API, runtime policy should return: REQUIRE_APPROVAL (threshold exceeded) trigger an approval workflow execute only after approval is granted This is the difference between API access and authorized business execution. Sample Policy Model (RBAC + ABAC + Approval) This POC policy model intentionally stays simple while demonstrating both coarse and fine-grained governance. 1) Coarse‑grained RBAC (roles → actions) FinanceAnalyst CreatePO up to 50,000 ViewVendor FinanceManager CreatePO up to 100,000 and/or approve higher spend 2) Fine‑grained ABAC (conditions at runtime) ABAC evaluates context such as region, classification, tenant boundary, and risk: 3) Approval injection (Agent‑level JIT execution) For higher-risk/high-impact actions, the fabric returns REQUIRE_APPROVAL rather than hard deny (when appropriate): How policies should be evaluated (deterministic order) To ensure predictable and auditable behavior, evaluate in a deterministic order: Tenant isolation & residency (ABAC hard deny first) Classification rules (deny or mask) RBAC entitlement validation Threshold/risk evaluation Approval injection (JIT step-up) This prevents approval workflows from bypassing foundational security boundaries such as tenant isolation or data sovereignty. Copilot Studio integration (enforcing runtime authorization) Copilot Studio can call external REST APIs using the HTTP Request node, including passing headers such as Authorization: Bearer <token> and binding response schema for branching logic. Copilot Studio also supports using flows with agents (“agent flows”) to extend capabilities and orchestrate actions. Option A (Recommended): Copilot Studio → Agent Flow (Power Automate) → Authorization Fabric Why: Flows are a practical place to handle token acquisition patterns, approval orchestration, and standardized logging. Topic flow: Extract user intent + parameters Call an agent flow that: calls /authorize returns decision payload Branch in the topic: If ALLOW → proceed to tool call If REQUIRE_APPROVAL → trigger approval flow; proceed only if approved If DENY → stop and explain policy reason Important: Tool execution must never be reachable through an alternate topic path that bypasses the authorization check. Option B: Direct HTTP Request node to Authorization Fabric Use the Send HTTP request node to call the authorization endpoint and branch using the response schema. This approach is clean, but token acquisition and secure secretless authentication are often simpler when handled via a managed integration layer (flow + connector). AI Foundry / Semantic Kernel integration (tool invocation gate) For Foundry/SK agents, the integration point is before tool execution. Semantic Kernel supports Azure AI agent patterns and tool integration, making it a natural place to enforce a pre-tool authorization check. Pseudo-pattern: Agent extracts intent + context Calls Authorization Fabric Enforces decision Executes tool only when allowed (or after approval) Telemetry & audit (what Security Architects will ask for) Even the best policy engine is incomplete without audit trails. At minimum, log: agentId, userUPN, action, resource decision + reason + policyIds approval outcome (if any) correlationId for downstream tool execution Why it matters: you now have a defensible answer to: “Why did an autonomous agent execute this action?” Security signal bonus: Denials, unusual approval rates, and repeated policy mismatches can also indicate prompt injection attempts, mis-scoped agents, or governance drift. What this enables (and why it scales) With a shared Authorization Fabric: Avoid duplicating authorization logic across agents Standardize decisions across Copilot Studio + Foundry agents Update governance once (policy change) and apply everywhere Make autonomy safer without blocking productivity Closing: Identity gets you who. Runtime authorization gets you whether/when/how. Copilot Studio can automatically create Entra agent identities (preview), improving identity governance and visibility for agents. But safe autonomy requires a runtime decision plane. Securing that plane as an Entra-protected endpoint is foundational for enterprise deployments. In enterprise environments, autonomous execution without runtime authorization is equivalent to privileged access without PIM—powerful, fast, and operationally risky.Ask Microsoft Anything: Why Cybersecurity Needs a New Security Stack for the AI Era with David Weston
David Weston leads Agentic Security at Microsoft, where he and his team build the AI models, autonomous agents, and evaluation systems redefining how defenders operate. At Microsoft since the Windows 7 era, he has worked across exploit mitigation design, malware analysis, APT research, and led security engineering for Windows, Xbox, Azure OS, and Microsoft's Offensive Security Research & Engineering group. His current work is leading teams training frontier security models, agentic security systems for defenders, and pushing AI-driven vulnerability discovery through Microsoft's Multi-Model Agentic Scanning Harness (MDASH). A longtime member of the research community and former CISA technical advisor, David is a regular presenter at BlueHat, Black Hat, and DEF CON. Key areas Dave and his team can discuss: The vision behind Project Perception How AI is changing the economics of cyber offense and defense Lessons learned from building MDASH and Microsoft's AI security initiatives Security-first AI development and deployment What's next for defenders as agentic systems become mainstream This will be a TEXT-BASED AMA, so ask your questions in the comment section down below and David and team will be answering via comment replies during the live hour!Authentication Context (Entra ID) Use case
Microsoft Entra ID has evolved rapidly over the last few years, with Microsoft continuously introducing new identity, access, and security capabilities as part of the broader Zero Trust strategy. While many organizations hold the necessary Entra ID and Microsoft 365 licenses (often through E3 or E5 bundles), a number of these advanced features remain under‑utilised or entirely unused. This is frequently due to limited awareness, overlapping capabilities or uncertainty about where and how these features provide real architectural value. One such capability which is not frequently used is Authentication Context. Although this feature is available for quite some time, it is often misunderstood or overlooked because it does not behave like traditional Conditional Access controls. Consider Authentication Context as a mobile “assurance tag” that connects a resource (or a particular access route to that resource) to one or several Conditional Access (CA) policies, allowing security measures to be enforced with resource-specific accuracy instead of broad, application-wide controls. Put simply, it permits step-up authentication only when users access sensitive information or perform critical actions, while maintaining a smooth experience for the “regular path.” When used intentionally, it enables resource‑level and scenario‑driven access control, allowing organizations to apply stronger authentication only where it is actually needed without increasing friction across the entire user experience. Not expensive Most importantly to use Authentication Context the minimum licensing requirement is Microsoft Entra ID Premium P1 which most customers already have this license. so you not need to convenience for higher license to utilize this feature. But do note Entra Premium 2 is needed if your Conditional Access policy uses advanced signals, such as: User or sign‑in risk (Identity Protection) Privileged Identity Management (PIM) protected roles Risk‑based Conditional Access policies The Workflow Architecturally, Authentication Context works when a claims request is made as part of token issuance commonly expressed via the acrs claim. When the request includes a specific context (for example c1), Entra evaluates CA policies that target that context and forces the required controls (MFA, device compliance, trusted location, etc.). The important constraint: the context must be requested/triggered by a supported workload (e.g., SharePoint) or by an application designed to request the claim; it is not an automatic “detect any action inside any app” feature. Lets look at few high level architecture reference 1. Define “assurance tiers” as contexts Create a small set of contexts (e.g., c1: Confidential Access, c2: Privileged Operations) and publish them for use by supported apps/services. 2. Bind contexts to resources Assign the context to the resource boundary you want to protect—most commonly SharePoint sites (directly or via sensitivity labels), so only those sites trigger the context. (e.g - Specific SharePoint sites like financials, agreements etc ) 3. Attach Conditional Access policies to the context Create CA policies that target the context and define enforcement requirements (Additional MFA strength, mandating device compliance, or location constraint through named locations etc.). The context is the “switch” that activates those policies at the right moment. 4. Validate runtime behavior and app compatibility Because authentication context can impact some client apps and flows, validate supported clients and known limitations (especially for SharePoint/OneDrive/Teams integrations). Some Practical Business Scenarios Scenario A — Confidential SharePoint Sites (M&A / Legal / HR) Problem: You want stronger controls for a subset of SharePoint sites without forcing those controls for all SharePoint access. Architect pattern: Tag the confidential site(s) with Authentication Context and apply a CA policy requiring stronger auth (e.g., compliant device + MFA) for that context. Pre-reqs: SharePoint Online support for authentication context; appropriate licensing and admin permissions; CA policies targeted to the context Scenario B — “Step-up” Inside a Custom Line-of-Business App Problem: Users can access the app normally, but certain operations (approval, export, privileged view) need elevated assurance. Architect pattern: Build the app on OpenID Connect/OAuth2 and explicitly request the authentication context (via acrs) when the user reaches the sensitive path; CA then enforces step-up. Pre-reqs: App integrated with Microsoft identity platform using OIDC/OAuth2; the app can trigger claims requests/handle claim challenges where applicable; CA policies defined for the context Scenario C — Granular “Resource-based” Zero Trust Without Blanket MFA Problem: Security wants strong controls on crown jewels, but business wants minimal prompts for routine work. Architect pattern: Use authentication context to enforce higher assurance only for protected resources (e.g., sensitive SharePoint sites). This provides least privilege at the resource boundary while reducing global friction. Pre-reqs: Clearly defined resource classification; authentication context configured and published; CA policies and monitoring. In a nutshell, Authentication Context allows organizations to move beyond broad, one‑size‑fits‑all Conditional Access policies and adopt a more precise, resource‑driven security model. By using it to link sensitive resources or protected access paths to stronger authentication requirements, organizations can improve security outcomes while minimizing unnecessary user friction. When applied deliberately and aligned to business‑critical assets, Authentication Context helps close the gap between licensing capability and real‑world value—turning underused Entra ID features into practical, scalable Zero Trust controls. If you find this useful, please do not forget to like and add your thoughts 🙂
Feature Request: Extend Security Copilot inclusion (M365 E5) to M365 A5 Education tenants
Background At Ignite 2025, Microsoft announced that Security Copilot is included for all Microsoft 365 E5 customers, with a phased rollout starting November 18, 2025. This is a significant step forward for security operations. The gap Microsoft 365 A5 for Education is the academic equivalent of E5 — it includes the same core security stack: Microsoft Defender, Entra, Intune, and Purview. However, the Security Copilot inclusion explicitly covers only commercial E5 customers. There is no public roadmap or timeline for extending this benefit to A5 education tenants. Why this matters Education institutions face the same cybersecurity threats as commercial organizations — often with fewer dedicated security resources. The A5 license was positioned as the premium security offering for education. Excluding it from Security Copilot inclusion creates an inequity between commercial and education customers holding functionally equivalent license tiers. Request We would like Microsoft to: Confirm whether Security Copilot inclusion will be extended to M365 A5 Education tenants If yes, provide an indicative timeline If no, clarify the rationale and what alternative paths exist for education customers Are other EDU admins in the same situation? Would appreciate any upvotes or comments to help raise visibility with the product team.Secure the age of AI: Redefining trust, data and access
There is no question that AI is transforming the enterprise: changing how data moves, how decisions are made, and how risk takes shape. As agents access, interpret, and act on sensitive data, unmanaged AI use expands and traditional boundaries blur. Kicking off our series on Securing Data and Access in the Era of AI, Microsoft Entra VP of Product Sinead O’Donovan and Microsoft Purview GM of Product Maithili Dandige explain why legacy security models fall short in the age of AI—and why you need a strategy that brings together identity, access, and data protection. Want to adopt and enable AI innovation with greater control and confidence? Join us to learn how leading organizations are securing access, protecting data, and establishing trust for the next generation of AI-powered work. This session is part of Securing data and access in the era of AI with Microsoft Entra and Microsoft Purview. View the full series for more insights to help you move from experimenting with AI to deploying it at scale, securing sensitive data, access, and AI usage.Securing data and access in the era of AI with Microsoft Entra and Microsoft Purview
As organizations move from experimenting with AI to deploying it at scale, securing sensitive data, access, and AI usage has become mission critical. In this series, Microsoft experts will show how Microsoft Entra and Microsoft Purview help you: Protect sensitive data across networks, apps, and AI interactions Govern access for users, applications, and AI agents Reduce risk while enabling innovation at scale Whether you're shaping your security strategy or implementing controls, you’ll walk away with the guidance you need to secure data and access to AI as one unified strategy. Now on demand! Secure the age of AI: Redefining trust, data and access Data and identity controls for the browser and network Unlock AI agents without sacrificing security Not able to watch here due to organizational policies? Use a personal account or visit each session page for an option to view on LinkedIn.Unlock AI agents without sacrificing security
AI agents are reaching into mailboxes, files, line-of-business apps, and the open web on behalf of your users—and the business wants more of them, faster. To scale agents safely, your security teams need to be able to verify each agent, govern what it can access, and enforce clear boundaries across every interaction. Learn how Microsoft Entra helps you discover shadow AI agents, govern agent permissions, keep BYOD and endpoint-based agents in scope, and apply Conditional Access to AI prompts and responses. Then see how Microsoft Purview provides visibility into agent activity, strengthens runtime data protection, helps detect agentic risk, and supports auditability across local agents developed on GitHub Copilot CLI, Claude Code, OpenAI Codex, and OpenClaw. Walk away with practical ways to unlock AI agents while keeping access and data protection aligned with your enterprise security needs. How do I participate? Select Add to Calendar to save the date, then click the Attend button to save your spot, receive event reminders, and participate in the Q&A. Not able to attend live? This session will be recorded and available on demand shortly after airing. Don't see Attend or Add to Calendar? Sign in to the Tech Community to join the conversation. If you are unable to watch the session here due to your organizational policies, you can also tune in on LinkedIn. This session is part of Securing data and access in the era of AI with Microsoft Entra and Microsoft Purview. View the full agenda for more insights to help you move from experimenting with AI to deploying it at scale, securing sensitive data, access, and AI usage.Data and identity controls for the browser and network
Sensitive data doesn't stay still. It moves through browsers, SaaS apps, generative AI tools, and prompts; often beyond the visibility of traditional controls. In this session, see how Microsoft Entra and Purview bring real-time visibility and control to sensitive data in motion across the network. You’ll learn how integrated data security and secure access controls can help reduce leakage risk, support responsible AI adoption, and enable modern work without slowing the business down. How do I participate? Select Add to Calendar to save the date, then click the Attend button to save your spot, receive event reminders, and participate in the Q&A. Not able to attend live? This session will be recorded and available on demand shortly after airing. Don't see Attend or Add to Calendar? Sign in to the Tech Community to join the conversation. If you can't view the session due to your organizational policies, you can also tune in on LinkedIn. This session is part of Securing data and access in the era of AI with Microsoft Entra and Microsoft Purview. View the full agenda for more insights to help you move from experimenting with AI to deploying it at scale, securing sensitive data, access, and AI usage.Stop identity attacks in real time with Microsoft Entra ID Protection
Modern identity security means stopping attacks before they escalate and extending protection beyond human users to apps and agentic identities across your identity fabric. Learn how Microsoft Entra ID Protection delivers premium, real-time identity protection with adaptive risk remediation, comprehensive detections, and expanded coverage for human and non-human identities. Powered by trillions of Microsoft Security signals and natively integrated with Microsoft Defender and Security Copilot workflows, Entra ID Protection enables faster and more accurate Conditional Access decisions that stop threats like lateral movement and privilege escalation before they spread. We'll show you how identity and security operations teams scale risk remediation with Entra ID, and how these capabilities extend across your broader identity security portfolio to strengthen protection in both cloud and hybrid environments. To learn more, read the Microsoft Entra ID Protection report. How do I participate? Registration is not required. Add this event to your calendar, then sign in to the Tech Community and select Attend to receive reminders. Post your questions in advance, or any time during the live broadcast.
